AboutSystems biology has become a powerful approach for drug discovery and development, bringing together OMICs data, structured “knowledge” databases of networks and pathways and tools for network analysis of OMICs data.
Significant effort is invested in the production and annotation of OMICs data and collection of biological information in a format of networks and pathways, which are available for research in the public domain or in proprietary sources.
However, OMICs data and network databases are only as useful as the analytical methods available for it's analysis.
Solution: computational biology methods for drug discovery
Clarivate Analytics, one of the leading providers of systems biology tools (such as MetaCore, MetaBase), launched “Computational Biology Methods for Drug Discovery” (CBDD) program which is focused on implementation of advanced state of the art approaches for network and pathway analysis of OMICs data.
With the CBDD program:
- Gain access to the best systems biology approaches Several of the most important methods developed for network analysis of OMICs data in past 10 years,implemented by the Clarivate Analytics Systems Biology Team.
- Get working tools
Algorithms implemented in convenient, well supported packages accessible from R which can be directly applied to networks and pathways represented in standard formats.
- Maximize utility of internal and external network/pathway information resources Increase the value of the analysis of OMICS data using a range of network methods
- Frees up more time by analysts to work on real analysis projects to deliver information on new drug targets, biomarker identification, patient stratification etc. rather than tool development